def main():
global default_cube
global goal
scrambled = scrambler(default, 3)
cube = Rubiks(scrambled, goal)
startTime = time.time()
result = astar_search(cube)
endTime = time.time()
print('solution is', Node.solution(result))
print('path is', Node.path(result))
print('걸린 시간 :', endTime - startTime)
def main():
global default_problem
global goal
global goal2
puzzle = EightPuzzle(default_problem, goal)
startTime = time.time()
result = depth_limited_search(puzzle, 30)
#result = breadth_first_tree_search(puzzle)
endTime = time.time()
print('solution is ', Node.solution(result))
print('path is', Node.path(result))
print('걸린 시간 :', endTime - startTime)
def sarkissian_hw6_2(problem):
node = Node(problem.initial)
if problem.goal_test(node.state):
return node
# heuristic function = the node's straight line distance to the goal node + the node's path cost
def h(_node):
return problem.straight_line_distance(_node.state) + _node.path_cost
frontier = NodePriorityQueue(h)
frontier.push(node)
visited = []
while len(frontier) > 0:
# pop a node out of the queue (this will always be the node with the lowest hueristic)
node = frontier.pop(
)[1] # NodePriorityQueue.pop() returns a tuple = (heuristic(node), node)
visited.append(node.state)
# if that node is the goal node, return the solution
if problem.goal_test(node.state):
print(f"Nodes Visited: {len(visited)}")
print(f"Distance Traveled: {node.path_cost} km")
return [
(n.state.lower(), h(n)) for n in node.path()
] # returns a list of 2-tuples (node.state, heuristic(node))
# if that node isn't the goal node, add its children to the frontier if they haven't already been visited
for child in node.expand(problem):
if child.state not in visited:
frontier.push(child)
return "FAILED"
def printPathAndSolution(result):
print('path is ...')
print(Node.path(result))
print('solution is ...')
print(Node.solution(result))
